A Robust Algorithm for Real Time Stereo Match Based on Mutual Information
Wenhui Zhou · Chuangan jishu xuebao · 2006
Stereo match algorithm is still an important and hot research topic in the computer vision domain. Most of the existing match algorithms are subject to similarity constraint. However, the non-uniform illumination, non-lambertian reflection in the off-road environments, and different camera gains or biases, all can violate the similarity constraint, and lead to match failure. Aiming at this case, a robust and real-time stereo match algorithm based on mutual information is proposed in view of practical applications. Mutual information is incorporated in the correlation based stereo match algorithm, and is transformed to summation form that can be used by the match algorithm. And, the mutual information is amended iteratively. At last, three luminance variance models are built to verify the validity of the proposed algorithm. Experiment results show this real-time algorithm is very robust, and can suppress the luminance difference of stereopsis successfully.